Research Interests

Current

Life experiences are transient, yet they often leave lasting footprints on the mind and brain. The brain recognizes, perceives, and translates the experiences, but is also shaped by them, and these processes are unique to every individual. These fingerprint-like cognitive dynamics, and how this variability emerges from brain network dynamics, are my biggest questions.

a. How do individual differences in cognitive state transitions shape how people interpret and adapt to internal and external experiences?

Even when facing identical environments, people perceive, evaluate, and internalize experiences differently. These variations likely arise from distinct configurations and transitions among cognitive processes such as attention allocation, mind wandering, and executive control. Cognition dynamically interacts with external inputs and gradually alters individual’s priors (or biases) carved as large-scale brain networks. I aim to understand how differences in cognitive state transitions, especially those governing internally oriented attention, give rise to stable behavioral and emotional patterns across individuals.

b. How can biologically grounded, multivariate representations of cognition capture latent individual differences?

Moving beyond categorical descriptions, I seek to represent individuals along latent cognitive dimensions derived from multivariate modeling of brain–behavior association. Such representations can reveal continuous axes of phenotypic variability and give cornerstone of neural mechanisms underlying individual uniqueness in cognitive dynamics described in question a. By anchoring these representations in biological substrates, I hope to study representations that are both predictive of individual behavior and interpretable in terms of underlying brain network organization.

c. How can integrating latent cognitive dimensions with brain network dynamics advance interpretable and personalized interventions?

By embedding latent cognitive factors within the dynamic architecture of brain networks, we may obtain more interpretable and biologically grounded markers of mental function. This integrated approach may offer interpretable markers of mental function that inform when, where, and for whom an intervention is most effective. Ultimately, my goal is to refine theoretical models of cognition while contributing to personalized strategies for mental-health assessment and intervention.

Brief descriptions of my current projects: Click ‘Current’ section of the Project menu.
Developing ideas: Click ‘Developing Ideas’ menu.

Second half of the master's program

My research began to take a new direction toward human neuroimaging and network-level approaches. It felt like entering an entirely new world. I didn’t even know how to open a raw T1 file at first. Everything felt foreign and overly abstract. But as I learned and practiced, I realized that what initially felt abstract was simply a different way to describe the same brain from a network/system level. It was interesting to see how distal brain regions synchronize and collectively generate human behavior as an output. Working with human MRI felt closer to real life. Instaed of focusing on a single circuit, I learned to analyze structural networks and closely followed functional analyses from non-invasive human MRI data.

Detailed information about the Parkinson’s disease project with Yonsei Severance Hospital: Click here

How would the individuals behave, think or feel? What would it mean to live with reduced drive or emotional flatness?
And how could those phenotype originate from the brain’s architecture?

While working on this project, I began to think deeply about disease complexity and individual heterogeneity. Patient with the same diagnosis could differ significantly in their symptoms and experiences. When I saw columns labeled ‘apathy’ or ‘motivation’ in the dataset (represented as numerical scores), I found it difficult to envision what those numbers actulally represented in an actual human being. Even after reading the questionnaires that was used to derive those scores, I kept wondering what these humans with that score/lables felt like from the inside. That gap between quantified measures and realities became one of the most interesting and unresolved questions for me.

First half of the master's program

In the early part of my master’s program, I was interested in how how the brain distributes energy with precise spatiotemporal coordination. Neurons fire within milliseconds, while vessels adjust over seconds, yet the resulting hemodynamic signal remains coherent across space and time.

How is such temporal precision and region specific coordination maintained in the neurovascular system?
What happens when the mechanical condition of this system begin to fail?

These questions led me to view neurovascular coupling as a dynamic control problem embedded in a hierarchical vascular network. I learned that the hierarchical organization of the brain vessel especially interesting. Vessels close to proximal branches (or small-order branches) are surrounded by smooth muscle cells with active contractility, but as vessels bifurcate into smaller perforating branches that penetrate deeper into the parenchyma, they are no longer wrapped by smooth muscle cells but by less contractile pericytes and even endothelial cells. This graudal loss of contractility makes deeper vessels respond more paassively. Then how does a neuronal response occurring deep in the tissue communicate upstream to secure the needed blood supply?

Before tackling these big questions, I wanted to start by examining one aspect of the system that mechanical properties of vessels being the boundary conditions for neurovascular coupling. I focused on how mechanical stress (originating from arterial stiffness) could distort the fine balance between neuronal demand and vascular response, even when pathology didn’t originate in the brain. Although I had to discontinue this work after developing severe mouse allergies, this experience was a turning point for me to shift toward network neuroscience.

For early stage ideas of that time: you can take a look here.

Undergraduate years

I majored biology, studying fundamental disciplines such as biochem, genetics, molecular, cellular, and developmental biology. My first exposure to neuroscience came during a short summer session at UC Berkeley, where I found how differently the brain could be studied compared to the biology I have known.

Later, during a fully funded exchange semester, returning at Berkeley, I took Genetic Factors of Neuropsychology, and this course changed how I thought about science. Until then, I had viewed “intervention” only through pharmacological means. But learning about the transition from DSM-IV to DSM-5 and how redefining autism as a spectrum could expand access to care and insurance coverage, was a eureka moment. I realized that research doesn’t need to end with a prescription to have an impact. Sometimes, understanding a disorder more accurately and carefully measuring its risk factors could directly improve quality of lives. That was the moment I began to see neuroscience not just as molecular mechanisms of the brain, but as a way to connect scientific understanding to real human outcomes.

At that time, I was obsessed with the idea:

What makes something truly interventible? Are there modifiable and systmic factors that can indirectly have an impact on brain health in broad populations?

Returning to Korea, I began my first full-time internship with this question in mind. For detailed project description: click here

Through this project, I began to study brain vasculature and realized how dynamic it is. I learned that blood flow can contribute to the clearance system (such as glympathic pathway). And the blood flow are altered by neurovascular coupling and pathological proteins. Growing interest in coordination between neural activity and local blood supply drove me to apply master program.